Mapa - parcelas
Edson Nilton de Moura SIlva JĂșnior
2023-12-09
Pacotes
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## âč Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(geobr)## Loading required namespace: sflibrary(sf)## Linking to GEOS 3.11.2, GDAL 3.6.2, PROJ 9.2.0; sf_use_s2() is TRUElibrary(terra)## terra 1.7.29
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## stampDados
Shappefiles
Saltinho
saltinho <- sf::st_read("saltinho.shp")## Reading layer `saltinho' from data source
## `G:\Meu Drive\UFPE\projeto mestrado\mestrado\saltinho.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 1 feature and 14 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: -35.19784 ymin: -8.739185 xmax: -35.16593 ymax: -8.712074
## Geodetic CRS: SIRGAS 2000saltinho## Simple feature collection with 1 feature and 14 fields
## Geometry type: POLYGON
## Dimension: XY
## Bounding box: xmin: -35.19784 ymin: -8.739185 xmax: -35.16593 ymax: -8.712074
## Geodetic CRS: SIRGAS 2000
## cd_cns_ nm_cns_ id_wcm categry group gvrnmn_
## 1 198 RESERVA BIOLĂGICA DE SALTINHO 6957 Reserva BiolĂłgica PI federal
## crtn_yr gid7
## 1 1983 300
## quality
## 1 Correto (O poligono corresponde ao memorial descritivo do ato legal de criação).
## legsltn dt_lt10 cod_111
## 1 Decreto nÂș 88744 de 21/09/1983 30/11/2007 0000.00.0198
## nm_rgnz date
## 1 Instituto Chico Mendes de Conservação da Biodiversidade 201909
## geometry
## 1 POLYGON ((-35.17557 -8.7146...saltinho %>%
ggplot() +
geom_sf()
Estados
estados <- geobr::read_state(showProgress = FALSE) ## Using year 2010estados## Simple feature collection with 27 features and 5 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -66.81025 ymin: -13.6937 xmax: -59.77435 ymax: -7.969294
## Geodetic CRS: SIRGAS 2000
## First 10 features:
## code_state abbrev_state name_state code_region name_region
## 1 11 RO RondĂŽnia 1 Norte
## 2 12 AC Acre 1 Norte
## 3 13 AM Amazonas 1 Norte
## 4 14 RR Roraima 1 Norte
## 5 15 PA ParĂĄ 1 Norte
## 6 16 AP AmapĂĄ 1 Norte
## 7 17 TO Tocantins 1 Norte
## 8 21 MA MaranhĂŁo 2 Nordeste
## 9 22 PI PiauĂ 2 Nordeste
## 10 23 CE CearĂĄ 2 Nordeste
## geom
## 1 MULTIPOLYGON (((-63.32721 -...
## 2 MULTIPOLYGON (((-73.18253 -...
## 3 MULTIPOLYGON (((-67.32609 2...
## 4 MULTIPOLYGON (((-60.20051 5...
## 5 MULTIPOLYGON (((-54.95431 2...
## 6 MULTIPOLYGON (((-51.1797 4....
## 7 MULTIPOLYGON (((-48.35878 -...
## 8 MULTIPOLYGON (((-45.84073 -...
## 9 MULTIPOLYGON (((-41.74605 -...
## 10 MULTIPOLYGON (((-41.16703 -...estados %>%
ggplot() +
geom_sf()
Continentes
continentes <- sf::st_read("World_Continents.shp")## Reading layer `World_Continents' from data source
## `G:\Meu Drive\UFPE\projeto mestrado\mestrado\World_Continents.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 8 features and 6 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -180 ymin: -89 xmax: 180 ymax: 83.6236
## Geodetic CRS: WGS 84continentes## Simple feature collection with 8 features and 6 fields
## Geometry type: MULTIPOLYGON
## Dimension: XY
## Bounding box: xmin: -180 ymin: -89 xmax: 180 ymax: 83.6236
## Geodetic CRS: WGS 84
## FID CONTINENT SQMI SQKM Shape__Are Shape__Len
## 1 1 Africa 11583462.7 30001150.8 3.353511e+13 49144798
## 2 2 Asia 17317280.1 44851729.0 1.145290e+14 311176819
## 3 3 Australia 2973612.2 7701651.1 9.652152e+12 29969539
## 4 4 North America 9339528.5 24189364.5 1.113144e+14 595152476
## 5 5 Oceania 165678.7 429107.6 6.581670e+11 26177519
## 6 6 South America 6856255.3 17757690.9 2.068439e+13 77372912
## 7 7 Antarctica 4754809.5 12314949.2 6.966421e+14 253068489
## 8 8 Europe 3821854.3 9898596.9 3.508924e+13 236911733
## geometry
## 1 MULTIPOLYGON (((35.48832 -2...
## 2 MULTIPOLYGON (((-180 68.980...
## 3 MULTIPOLYGON (((158.8822 -5...
## 4 MULTIPOLYGON (((-81.67847 7...
## 5 MULTIPOLYGON (((180 -16.965...
## 6 MULTIPOLYGON (((-67.20889 -...
## 7 MULTIPOLYGON (((-180 -84.30...
## 8 MULTIPOLYGON (((23.84853 35...continentes %>%
ggplot() +
geom_sf()
Trilhas
trilhas <- sf::st_read("Trilhas.shp")## Reading layer `Trilhas' from data source
## `G:\Meu Drive\UFPE\projeto mestrado\mestrado\Trilhas.shp' using driver `ESRI Shapefile'
## Simple feature collection with 4 features and 11 fields
## Geometry type: LINESTRING
## Dimension: XYZ
## Bounding box: xmin: -35.19158 ymin: -8.737647 xmax: -35.16856 ymax: -8.715277
## z_range: zmin: 0 zmax: 0
## Geodetic CRS: WGS 84trilhas## Simple feature collection with 4 features and 11 fields
## Geometry type: LINESTRING
## Dimension: XYZ
## Bounding box: xmin: -35.19158 ymin: -8.737647 xmax: -35.16856 ymax: -8.715277
## z_range: zmin: 0 zmax: 0
## Geodetic CRS: WGS 84
## Name descriptio timestamp begin end altitudeMo tessellate extrude
## 1 Trilha 1 <NA> <NA> <NA> <NA> <NA> 1 0
## 2 Trilha 2 <NA> <NA> <NA> <NA> <NA> 1 0
## 3 Trilha 3 <NA> <NA> <NA> <NA> <NA> 1 0
## 4 Trilha 4 <NA> <NA> <NA> <NA> <NA> 1 0
## visibility drawOrder icon geometry
## 1 -1 NA <NA> LINESTRING Z (-35.18349 -8....
## 2 -1 NA <NA> LINESTRING Z (-35.19158 -8....
## 3 -1 NA <NA> LINESTRING Z (-35.18818 -8....
## 4 -1 NA <NA> LINESTRING Z (-35.17173 -8....trilhas %>%
ggplot() +
geom_sf(aes(color = Name)) +
labs(color = NULL)
Parcelas
parcelas <- sf::st_read("Parcelas.shp")## Reading layer `Parcelas' from data source
## `G:\Meu Drive\UFPE\projeto mestrado\mestrado\Parcelas.shp'
## using driver `ESRI Shapefile'
## Simple feature collection with 16 features and 11 fields
## Geometry type: LINESTRING
## Dimension: XYZ
## Bounding box: xmin: -35.19158 ymin: -8.737648 xmax: -35.16721 ymax: -8.714365
## z_range: zmin: 0 zmax: 0
## Geodetic CRS: WGS 84parcelas## Simple feature collection with 16 features and 11 fields
## Geometry type: LINESTRING
## Dimension: XYZ
## Bounding box: xmin: -35.19158 ymin: -8.737648 xmax: -35.16721 ymax: -8.714365
## z_range: zmin: 0 zmax: 0
## Geodetic CRS: WGS 84
## First 10 features:
## Name descriptio timestamp begin end altitudeMo tessellate
## 1 Transecto 1 - trilha 1 <NA> <NA> <NA> <NA> <NA> 1
## 2 Transecto 2 - trilha 1 <NA> <NA> <NA> <NA> <NA> 1
## 3 Transecto 3 - trilha 1 <NA> <NA> <NA> <NA> <NA> 1
## 4 Transecto 4 - trilha 1 <NA> <NA> <NA> <NA> <NA> 1
## 5 Transecto 1 - trilha 2 <NA> <NA> <NA> <NA> <NA> 1
## 6 Transecto 2 - trilha 2 <NA> <NA> <NA> <NA> <NA> 1
## 7 Transecto 3 - trilha 2 <NA> <NA> <NA> <NA> <NA> 1
## 8 Transecto 4 - trilha 2 <NA> <NA> <NA> <NA> <NA> 1
## 9 Transecto 5 - trilha 2 <NA> <NA> <NA> <NA> <NA> 1
## 10 Transecto 6 - trilha 2 <NA> <NA> <NA> <NA> <NA> 1
## extrude visibility drawOrder icon geometry
## 1 0 -1 NA <NA> LINESTRING Z (-35.1734 -8.7...
## 2 0 -1 NA <NA> LINESTRING Z (-35.17659 -8....
## 3 0 -1 NA <NA> LINESTRING Z (-35.18014 -8....
## 4 0 -1 NA <NA> LINESTRING Z (-35.18349 -8....
## 5 0 -1 NA <NA> LINESTRING Z (-35.17363 -8....
## 6 0 -1 NA <NA> LINESTRING Z (-35.17716 -8....
## 7 0 -1 NA <NA> LINESTRING Z (-35.18082 -8....
## 8 0 -1 NA <NA> LINESTRING Z (-35.18437 -8....
## 9 0 -1 NA <NA> LINESTRING Z (-35.18797 -8....
## 10 0 -1 NA <NA> LINESTRING Z (-35.19158 -8....parcelas %>%
ggplot() +
geom_sf(aes(color = Name)) +
labs(color = NULL)
Imagem de satélite
saltinho_sat <- terra::rast("Saltinho.tif")
saltinho_sat## class : SpatRaster
## dimensions : 6225, 8442, 4 (nrow, ncol, nlyr)
## resolution : 5.475979e-06, 5.475979e-06 (x, y)
## extent : -35.20319, -35.15696, -8.744113, -8.710025 (xmin, xmax, ymin, ymax)
## coord. ref. : lon/lat SIRGAS 2000 (EPSG:4674)
## source : Saltinho.tif
## names : Saltinho_1, Saltinho_2, Saltinho_3, Saltinho_4ggplot() +
tidyterra::geom_spatraster_rgb(data = saltinho_sat)## SpatRaster resampled to ncells = 500992
Mapa
Mapa do Brasil-América do Sul
br <- ggplot()+
geom_sf(data = continentes, color = "black", fill = "gray40") +
geom_sf(data = estados, color = "black", fill = "white") +
geom_sf(data = estados %>% dplyr::filter(name_state == "Pernambuco"), fill = "gray", color = "black") +
geom_rect(aes(xmin = -41.25, xmax = -34.9, ymin = -9.5, ymax = -7.25, color = "Pernambuco"), fill = "red", alpha = 0.4) +
scale_color_manual(values = "red") +
coord_sf(xlim = c(-80, -35), ylim = c(-55, 12)) +
labs(color = NULL,
fill = NULL) +
theme_classic() +
theme(legend.position = "bottom",
axis.text = element_text(color = "black"),
plot.background = element_blank(),
panel.background = element_blank(),
plot.margin = margin(0.5, 0.5, 0.5, 0.5, "cm"))
br
Mapa de Pernambuco
gg_pe <- ggplot() +
geom_sf(data = estados, color = "black", fill = "white") +
geom_sf(data = estados %>% dplyr::filter(name_state == "Pernambuco"), aes(fill = "Pernambuco"), color = "black") +
tidyterra::geom_spatraster_rgb(data = saltinho_sat) +
geom_rect(aes(xmin = -35.20, xmax = -35.16, ymin = -8.7426, ymax = -8.712, color = "REBio Saltinho"), fill = "red", alpha = 0.4) +
coord_sf(xlim = c(-41.25, -34.9), ylim = c(-9.5, -7.25)) +
labs(color = NULL,
fill = NULL) +
scale_color_manual(values = "red") +
scale_fill_manual(values = "gray") +
ggspatial::annotation_scale(location = "br", height = unit(0.3,"cm"), bar_cols = c("black", "white")) +
theme_classic() +
theme(legend.position = "bottom",
axis.text = element_text(color = "black"),
plot.background = element_blank(),
panel.background = element_blank(),
plot.margin = margin(0.5, 0.5, 0.5, 0.5, "cm"))## SpatRaster resampled to ncells = 500992gg_pe
Mapa de Saltinho
Transformando os dados das trilhas e das parcelas em dataframe
trilhas_df <- trilhas %>% sf::st_coordinates() %>%
as.data.frame() %>%
dplyr::mutate(Trilha = L1 %>% as.character(),
Trilha = paste0("Trilha ", Trilha)) %>%
dplyr::select(c(1:2, 5))
parcelas_df <- parcelas %>% sf::st_coordinates() %>%
as.data.frame() %>%
dplyr::mutate(Parcela = L1 %>% as.character())
trilhas_df## X Y Trilha
## 1 -35.18349 -8.715277 Trilha 1
## 2 -35.18014 -8.718307 Trilha 1
## 3 -35.17658 -8.721506 Trilha 1
## 4 -35.17340 -8.724380 Trilha 1
## 5 -35.19158 -8.716887 Trilha 2
## 6 -35.18798 -8.719664 Trilha 2
## 7 -35.18437 -8.722436 Trilha 2
## 8 -35.18082 -8.725163 Trilha 2
## 9 -35.17716 -8.727953 Trilha 2
## 10 -35.17362 -8.730673 Trilha 2
## 11 -35.18818 -8.725463 Trilha 3
## 12 -35.18454 -8.728118 Trilha 3
## 13 -35.18081 -8.730817 Trilha 3
## 14 -35.17722 -8.733469 Trilha 3
## 15 -35.17173 -8.734406 Trilha 4
## 16 -35.16856 -8.737647 Trilha 4parcelas_df## X Y Z L1 Parcela
## 1 -35.17340 -8.724380 0 1 1
## 2 -35.17343 -8.724467 0 1 1
## 3 -35.17350 -8.724516 0 1 1
## 4 -35.17352 -8.724606 0 1 1
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## 414 -35.17012 -8.733306 0 16 16Mapa
salt <- ggplot() +
geom_spatraster_rgb(data = saltinho_sat) +
geom_sf(data = saltinho, aes(color = "REBio Saltinho"), fill = NA, linewidth = 1.5) +
coord_sf(xlim = c(-35.20, -35.16), ylim = c(-8.7426, -8.712)) +
scale_color_manual(values = "red") +
labs(color = NULL) +
ggnewscale::new_scale_colour() +
geom_line(data = trilhas_df, aes(X, Y, color = Trilha), linewidth = 1.25, show.legend = FALSE) +
scale_color_manual(values = rep("yellow", 4)) +
labs(color = NULL,
x = NULL,
y = NULL) +
ggnewscale::new_scale_colour() +
geom_line(data = parcelas_df, aes(X, Y, color = Parcela), show.legend = FALSE) +
scale_color_manual(values = rep("yellow", 16)) +
labs(color = NULL,
x = NULL,
y = NULL) +
guides(color = guide_legend(order = 2)) +
ggspatial::annotation_scale(location = "br", height = unit(0.3,"cm"), bar_cols = c("black", "white")) +
theme_classic() +
theme(legend.position = "bottom",
axis.text = element_text(color = "black"),
plot.background = element_blank(),
panel.background = element_blank(),
plot.margin = margin(0.5, 0.5, 0.5, 0.5, "cm"))## SpatRaster resampled to ncells = 500992salt
Unificando os mapas
Estado de Pernambuco + Saltinho
mapa_1 <- gg_pe + salt + patchwork::plot_layout(nrow = 2)
mapa_1
Fundo de para o mapa final
df <- data.frame(x = 1, y = 1)
gg <- df %>%
ggplot(aes(x, y)) +
theme(panel.background = element_rect(color = "white", fill = "white"),
plot.background = element_rect(color = "white", fill = "white"),
axis.title = element_text(color = "white"),
axis.text = element_text(color = "white"))
gg 
ggsave(filename = "vazio.png")## Saving 10 x 8 in imageMapa final
gg +
draw_plot(mapa_1, width = 0.5, height = 1, x = 0, y = 0) +
draw_plot(br, width = 0.425, height = 0.925, x = 0.48, y = 0.05)
ggsave(filename = "saltinho_mapa_trilhas.png", height = 12, widt = 14)Salvando as coordenadas em bases de dados
Trilhas
trilhas_xlsx <- trilhas %>%
sf::st_coordinates() %>%
as.data.frame() %>%
dplyr::mutate(Longitude = X,
Latitude = Y,
Trilha = L1 %>% as.character(),
Ponto = c(seq(1:4) %>% sort(decreasing = TRUE),
seq(1:6) %>% sort(decreasing = TRUE),
seq(1:4) %>% sort(decreasing = TRUE),
seq(1:2) %>% sort(decreasing = TRUE))) %>%
dplyr::select(5:8) %>%
dplyr::arrange(Trilha, Ponto)
trilhas_xlsx## Longitude Latitude Trilha Ponto
## 1 -35.17340 -8.724380 1 1
## 2 -35.17658 -8.721506 1 2
## 3 -35.18014 -8.718307 1 3
## 4 -35.18349 -8.715277 1 4
## 5 -35.17362 -8.730673 2 1
## 6 -35.17716 -8.727953 2 2
## 7 -35.18082 -8.725163 2 3
## 8 -35.18437 -8.722436 2 4
## 9 -35.18798 -8.719664 2 5
## 10 -35.19158 -8.716887 2 6
## 11 -35.17722 -8.733469 3 1
## 12 -35.18081 -8.730817 3 2
## 13 -35.18454 -8.728118 3 3
## 14 -35.18818 -8.725463 3 4
## 15 -35.16856 -8.737647 4 1
## 16 -35.17173 -8.734406 4 2trilhas_xlsx %>% openxlsx::write.xlsx("trilhas.xlsx")Parcelas
parcelas_xlsx <- parcelas %>%
sf::st_coordinates() %>%
as.data.frame() %>%
dplyr::mutate(Longitude = X,
Latitude = Y,
Parcela = L1 %>% as.character(),
Trilha = c(rep("1", 103),
rep("2", 156),
rep("3", 103),
rep("4", 52))) %>%
dplyr::select(5:8)
parcelas_xlsx## Longitude Latitude Parcela Trilha
## 1 -35.17340 -8.724380 1 1
## 2 -35.17343 -8.724467 1 1
## 3 -35.17350 -8.724516 1 1
## 4 -35.17352 -8.724606 1 1
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## 413 -35.17020 -8.733338 16 4
## 414 -35.17012 -8.733306 16 4parcelas_xlsx %>% openxlsx::write.xlsx("parcelas.xlsx")